Skip to content

A multi-platform web-app for managing tasks and goals using the Mikado Method.

Notifications You must be signed in to change notification settings

SEG491X-W2023-T42/mikado-machine

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

mikado-machine

Introduction

The Mikado Method is a software development methodology that aims to address complex problems in a structured and systematic manner. It helps teams to understand the dependencies and relationships between different parts of a system and prioritize the changes that need to be made. Traditionally, the Mikado Method is performed with pen and paper, which was intended to facilitate the process with no upfront investment for Agile performance. The client for this project, Andriy Drozdyuk, who is a machine learning and deep learning programmer, is seeking an electronic method to perform the Mikado Method to aid in code refactoring activities for his work.

Project Wiki

Team organizational information can be found in the docs/ repo.

Topic Description
Team Documents related to team structure
Onboarding Documents related to new developer onboarding
Development Process Documents related to software development process
Meeting Minutes Brief minutes for all our team meetings

More to come later.

Project Documents

Doc Description
Engineering Document 1 Needs, Problem Statement, Metrics, Benchmarking, and Target Specification
Engineering Document 2 Iteration 1 Agile Document
Engineering Document 3 Iteration 2 Agile Document
Project Management Gantt Chart Gantt chart for tracking tasks and planning over time
Formal Time Sheet Time tracking

License

See the license here. The license applies to all files in this repository unless stated otherwise.

This project is currently intended to be visible-source and not open-contribution like SQLite. This is currently in place to make it possible for our professor to evaluate our team project without outside interference. Derivative works are strongly discouraged, and the license will automatically assign us more rights than it gives you. At the end of 2023, we may decide to release it as open-source with/without a premium version. In the meantime, early testers are welcome to play with the beta version hosted on the cloud, though major breaking changing may occur regularly, including those affecting data.

References

Wiki was created referencing the public template at shekhargulati/project-wiki-template